Gastrointestinal Stromal Tumors: What Is the Best Sequence of TKIs?

Advanced gastrointestinal stromal tumor: reliable classification of imatinib plasma trough concentration via machine learning

AIM

Patients with advanced gastrointestinal stromal tumors (GISTs) exhibiting an imatinib plasma trough concentration (IM Cmin) under 1100 ng/ml may show a reduced drug response rate, leading to the suggestion of monitoring for IM Cmin. Consequently, the objective of this research was to create a customized IM Cmin classification model for patients with advanced GISTs from China.

METHODS

Initial data and laboratory indicators from patients with advanced GISTs were gathered, and the above information was segmented into a training set, validation set, and testing set in a 6:2:2 ratio. Key variables associated with IM Cmin were identified to construct the classification model using the least absolute shrinkage and selection operator (LASSO) regression and forward stepwise binary logistic regression. Within the training and validation sets, nine ML classification models were constructed via the resampling method and underwent comparison through the Brier scores, the areas under the receiver-operating characteristic curve (AUROC), the decision curve, and the precision-recall (AUPR) curve to determine the most suitable model for this dataset. Two methods of internal validation were used to assess the most suitable model's classification performance: tenfold cross-validation and random split-sample validation (test set), and the value of the test set AUROC was used to evaluate the model's classification performance.

RESULTS

Six key variables (gender, daily IM dose, metastatic site, red blood cell count, platelet count, and percentage of neutrophils) were ultimately selected to construct the classification model. In the validation set, it is found by comparison that the Extreme Gradient Boosting (XGBoost) model has the largest AUROC, the lowest Brier score, the largest area under the decision curve, and the largest AUPR value. Furthermore, as evaluated via internal verification, it also performed well in the test set (AUROC = 0.725).

CONCLUSION

For patients with advanced GISTs who receive IM, initial data and laboratory indicators could be used to accurately estimate whether the IM Cmin is below 1100 ng/ml. The XGBoost model may stand a chance to assist clinicians in directing the administration of IM.

Ripretinib for the treatment of advanced, imatinib-resistant gastrointestinal stromal tumors

Discovery of constitutive activation of KIT/PDGFRA tyrosine kinases in gastrointestinal stromal tumors (GISTs) leads to the development of the targeted drug imatinib. However, the inevitable development of imatinib resistance remains a major issue. Ripretinib is a novel targeted drug that inhibits the activities of a broad spectrum of drug-resistant KIT/PDGFRA mutants. It was approved in 2020 and is currently recommended by major international guidelines as the fourth-line and beyond therapy for advanced GISTs. Emerging evidence shows that ripretinib is superior to sunitinib as a second-line treatment for KIT exon 11-mutated GISTs due to its activity against highly heterogeneous frequently occurring secondary mutations. This review summarizes current data on the use of ripretinib to treat advanced imatinib-resistant GISTs. We also propose future research directions to improve the targeted GIST treatment.

Hematologic toxicities of sunitinib in patients with gastrointestinal stromal tumors: a systematic review and meta-analysis

PURPOSE

Sunitinib offers a significant survival benefit to patients with imatinib-resistant gastrointestinal stromal tumors (GIST). However, the incidence and risk of sunitinib-induced hematologic toxicities in such a population are often overlooked and have not been well characterized. This meta-analysis was performed to assess the summary incidence and risk of hematologic toxicities secondary to sunitinib in patients with GIST.

METHODS

Searches were performed in PubMed, Embase, Cochrane Library, and Web of Science as well as ClinicalTrials.gov to identify relevant studies up to April 2022. Studies with adequate safety profile, including anemia, neutropenia, and thrombocytopenia, were included to calculate the pooled incidence, relative risk (RR), and corresponding 95% confidence intervals (CIs). This study was registered with PROSPERO under number CRD42022328202.

RESULTS

A total of 2593 patients from 13 studies were included in the present meta-analysis. For patients with GIST assigned to sunitinib, the overall incidences of all-grade anemia, neutropenia, and thrombocytopenia were 26.2% (95% CI, 14.9-39.4%), 41.8% (95% CI, 29.0-55.1%), and 36.4% (95% CI, 22.8-51.1%), respectively. Regarding high-grade (grades 3 and 4) events, there were 4.7% (95% CI, 3.8-5.6%) for anemia, 9.3% (95% CI, 5.6-13.7%) for neutropenia and 5.0% (95% CI, 2.9-7.3%) for thrombocytopenia. Compared to placebo arms, sunitinib was related to an increased risk of high-grade neutropenia with an RR of 10.39 (95% CI, 1.53-70.72; p = 0.017).

CONCLUSIONS

Sunitinib carries a relatively high incidence of hematologic toxicities and a substantial increased risk of high-grade neutropenia in patients with GIST. Appropriate prevention and management seem to be inevitable.

[Abdominal soft tissue tumors]

Gastrointestinal stromal tumors are the most common mesenchymal tumors in the abdomen and occur in Germany with an incidence of 10 to 15 cases per million inhabitants. Clear identification and characterization are of major importance for the prognosis and therapy of patients. Similarly, they have to be differentiated from other mesenchymal neoplasias such as leiomyomatous, neurogenic, adipocytic, and fibroblastic tumors. Additionally, the number of translocation positive neoplasias is increasing, requiring the use of adequate molecular assays. The aim of this paper is to give practical advice for their identification. Reference pathology is one possibility to support the correct diagnosis.